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Register a new userMulti-Step Reasoning Over Unstructured Text with Beam Dense Retrieval
منطق متعدد الخطوات حول النص غير منظم مع استرجاع شعاع كثيف
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غالبا ما يتطلب الإجابة على السؤال المجمع إيجاد سلسلة من التفكير يتكون من قطع أدلة متعددة.تتضمن الأساليب الحالية نقاط قوة المعرفة والنص غير منظم، بافتراض النص النحاسي نصف منظم.بناء على طرق استرجاع كثيفة، نقترح نهجا جديدا استرجاع متعدد الخطوات (BEAMDR) يشكل بشكل متكرر سلسلة دليل من خلال البحث في شعاع في تمثيلات كثيفة.عند تقييمها على الإجابة على السؤال المتعدد القفز، فإن Beamdr منافسة النظم الحديثة، دون استخدام أي معلومات شبه منظمة.من خلال تكوين الاستعلام في الفضاء الكثيف، يلتقط Beamdr العلاقات الضمنية بين الأدلة في سلسلة المنطق.الرمز متاح في HENREZHAO5852 / BEAMDR.
Complex question answering often requires finding a reasoning chain that consists of multiple evidence pieces. Current approaches incorporate the strengths of structured knowledge and unstructured text, assuming text corpora is semi-structured. Building on dense retrieval methods, we propose a new multi-step retrieval approach (BeamDR) that iteratively forms an evidence chain through beam search in dense representations. When evaluated on multi-hop question answering, BeamDR is competitive to state-of-the-art systems, without using any semi-structured information. Through query composition in dense space, BeamDR captures the implicit relationships between evidence in the reasoning chain. The code is available at https://github.com/ henryzhao5852/BeamDR.
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